Development of DNDC-BC model to estimate greenhouse gas emissions from rice paddy fields under combination of biochar and controlled irrigation management.

Acknowledgments This work was supported by the National Natural Science Foundation of China 608 (51879076), SuperG (Nr: 774124; funded under EU Horizon 2020 programme), the Fundamental Research Funds for the Central Universities (B220203009), the Postgraduate Research & Practice Program of Jiangsu Province (KYCX22_0669), the Water Conservancy Science and Technology Project of Jiangxi Province 12 (202124ZDKT09). Thanks to the late Professor Changsheng Li who provided the source code of DNDC and corresponding support. We thank the China Scholarship Council (CSC) for providing a scholarship to Zewei Jiang.Peer reviewedPublisher PD

Differences in resting-state brain networks and gray matter between APOE ε2 and APOE ε4 carriers in non-dementia elderly

BackgroundApolipoprotein E (APOE) ε2 and APOE ε4 are the most distinct alleles among the three APOE alleles, both structurally and functionally. However, differences in cognition, brain function, and brain structure between the two alleles have not been comprehensively reported in the literature, especially in non-demented elderly individuals.MethodsA neuropsychological test battery was used to evaluate the differences in cognitive performance in five cognitive domains. Independent component analysis (ICA) and voxel-based morphometry (VBM) were used separately to analyze resting-state functional magnetic resonance imaging (rs-fMRI) data and the structure MRI data between the two groups. Finally, correlations between differential brain regions and neuropsychological tests were calculated.ResultsAPOE ε2 carriers had better cognitive performance in general cognitive, memory, attention, and executive function than APOE ε4 carriers (all p < 0.05). In ICA analyses of rs-fMRI data, the difference in the resting-state functional connectivity (rsFC) between two groups is shown in 7 brain networks. In addition, VBM analyses of the T1-weighted image revealed that APOE ε2 carriers had a larger thalamus and right postcentral gyrus volume and a smaller bilateral putamen volume than APOE ε4 carriers. Finally, differences in brain function and structure may be might be the reason that APOE ε2 carriers are better than APOE ε4 carriers in cognitive performance.ConclusionThese findings suggest that there are significant differences in brain function and structure between APOE ε2 carriers and APOE ε4 carriers, and these significant differences are closely related to their cognitive performance

Simulating soil salinity dynamics, cotton yield and evapotranspiration under drip irrigation by ensemble machine learning

Cotton is widely used in textile, decoration, and industry, but it is also threatened by soil salinization. Drip irrigation plays an important role in improving water and fertilization utilization efficiency and ensuring crop production in arid areas. Accurate prediction of soil salinity and crop evapotranspiration under drip irrigation is essential to guide water management practices in arid and saline areas. However, traditional hydrological models such as Hydrus require more variety of input parameters and user expertise, which limits its application in practice, and machine learning (ML) provides a potential alternative. Based on a global dataset collected from 134 pieces of literature, we proposed a method to comprehensively simulate soil salinity, evapotranspiration (ET) and cotton yield. Results showed that it was recommended to predict soil salinity, crop evapotranspiration and cotton yield based on soil data (bulk density), meteorological factors, irrigation data and other data. Among them, meteorological factors include annual average temperature, total precipitation, year. Irrigation data include salinity in irrigation water, soil matric potential and irrigation water volume, while other data include soil depth, distance from dripper, days after sowing (for EC and soil salinity), fertilization rate (for yield and ET). The accuracy of the model has reached a satisfactory level, R2 in 0.78-0.99. The performance of stacking ensemble ML was better than that of a single model, i.e., gradient boosting decision tree (GBDT); random forest (RF); extreme gradient boosting regression (XGBR), with R2 increased by 0.02%-19.31%. In all input combinations, other data have a greater impact on the model accuracy, while the RMSE of the S1 scenario (input without meteorological factors) without meteorological data has little difference, which is -34.22%~19.20% higher than that of full input. Given the wide application of drip irrigation in cotton, we recommend the application of ensemble ML to predict soil salinity and crop evapotranspiration, thus serving as the basis for adjusting the irrigation schedule

The mid-Miocene Zhangpu biota reveals an outstandingly rich rainforest biome in East Asia

During the Mid-Miocene Climatic Optimum [MMCO, ~14 to 17 million years (Ma) ago], global temperatures were similar to predicted temperatures for the coming century. Limited megathermal paleoclimatic and fossil data are known from this period, despite its potential as an analog for future climate conditions. Here, we report a rich middle Miocene rainforest biome, the Zhangpu biota (~14.7 Ma ago), based on material preserved in amber and associated sedimentary rocks from southeastern China. The record shows that the mid-Miocene rainforest reached at least 24.2°N and was more widespread than previously estimated. Our results not only highlight the role of tropical rainforests acting as evolutionary museums for biodiversity at the generic level but also suggest that the MMCO probably strongly shaped the East Asian biota via the northern expansion of the megathermal rainforest biome. The Zhangpu biota provides an ideal snapshot for biodiversity redistribution during global warming

Graphene-Based Nanocomposites for Energy Storage

Since the first report of using micromechanical cleavage method to produce graphene sheets in 2004, graphene/graphene-based nanocomposites have attracted wide attention both for fundamental aspects as well as applications in advanced energy storage and conversion systems. In comparison to other materials, graphene-based nanostructured materials have unique 2D structure, high electronic mobility, exceptional electronic and thermal conductivities, excellent optical transmittance, good mechanical strength, and ultrahigh surface area. Therefore, they are considered as attractive materials for hydrogen (H2) storage and high-performance electrochemical energy storage devices, such as supercapacitors, rechargeable lithium (Li)-ion batteries, Li–sulfur batteries, Li–air batteries, sodium (Na)-ion batteries, Na–air batteries, zinc (Zn)–air batteries, and vanadium redox flow batteries (VRFB), etc., as they can improve the efficiency, capacity, gravimetric energy/power densities, and cycle life of these energy storage devices. In this article, recent progress reported on the synthesis and fabrication of graphene nanocomposite materials for applications in these aforementioned various energy storage systems is reviewed. Importantly, the prospects and future challenges in both scalable manufacturing and more energy storage-related applications are discussed

Ammonia Sensing Behaviors of TiO2-PANI/PA6 Composite Nanofibers

Titanium dioxide-polyaniline/polyamide 6 (TiO2-PANI/PA6) composite nanofibers were prepared by in situ polymerization of aniline in the presence of PA6 nanofibers and a sputtering-deposition process with a high purity titanium sputtering target. TiO2-PANI/PA6 composite nanofibers and PANI/PA6 composite nanofibers were fabricated for ammonia gas sensing. The ammonia sensing behaviors of the sensors were examined at room temperature. All the results indicated that the ammonia sensing property of TiO2-PANI/PA6 composite nanofibers was superior to that of PANI/PA6 composite nanofibers. TiO2-PANI/PA6 composite nanofibers had good selectivity to ammonia. It was also found that the content of TiO2 had a great influence on both the morphology and the sensing property of TiO2-PANI/PA6 composite nanofibers

Loneliness is related to smaller gray matter volumes in ACC and right VLPFC in people with major depression:a UK biobank study

The anterior cingulate cortex (ACC) and right ventrolateral prefrontal cortex (VLPFC) are thought to have important roles in loneliness (feeling of social isolation/exclusion) experience or regulation and in the pathophysiology of their disturbance in major depressive disorder (MDD). However, the structural abnormalities of these regions and the correlates with loneliness in MDD across the healthy population have not fully been clarified. The study analyzed the link between loneliness and gray matter volumes (GMVs) in the ACC and right VLPFC among 1,005 patients with MDD and 7,247 healthy controls (HCs) using UK Biobank data. Significant reductions in GMV in the right VLPFC were found in MDD males compared to HCs. MDD males also showed a higher association between loneliness and reduced GMVs in the right VLPFC and bilateral ACC than HCs. No such associations were found in MDD females. The findings suggest that loneliness may influence brain structures crucial for emotion experience and regulation, particularly in middle-older aged men with MDD. This highlights the potential adverse effects of loneliness on brain structure in MDD and suggests that social engagement could have a positive impact.</p

Distinct Packings of Supramolecular Building Blocks in Metal–Organic Frameworks Based on Imidazoledicarboxylic Acid

When the supramolecular building block packings (face-centered, body-centered, and primitive cubic) with different interactions (hydrogen and coordination bonding) were controlled, four new structures based on octahedral M^II (M = Zn, Ni, Mn) and imidazoledicarboxylate were constructed. The interaction modes between the supramolecular building blocks affect the water stability of the structures. Furthermore, with uncoordinated carboxylate O atoms in the structures, these compounds demonstrate a strong capability of capturing metal ions in the solution